A Longitudinal Study on Psychometric Properties of the Simplified Chinese Version of FACT-Hep for Patients with Hepatocellular Carcinoma by Classical Test Theory and Generalizability Theory

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Authors: Yongcun Wang, Shulin Ding, Qiong Meng, yingli cun, Gaofeng Li, Ying Chen, Chonghua Wan
Cited by: 0
References: 39

Abstract

Background: Health-related Quality of life (HRQOL) is now concerned worldwide in cancer clinical fields, with the specific scales for patients with hepatocellular carcinoma in China being seldom and no formal validation of Chinese Version of the FACT-Hep. This study was aimed to validate the Chinese FACT-Hep based on both Classical Test Theory and Generalizability Theory to rationalize its use in the Chinese population. Methods: One hundred and fourteen in-patients with hepatocellular carcinoma were measured three times before and after treatments using the FACT-Hep. The FACT-Hep was evaluated by Cronbach α, Pearson correlation, intra-class correlation (ICC), and paired-t tests with standardized response mean. The Generalizability Theory was also applied to addresses the dependability of measurements deeply by estimation of multiple sources of variance. Results: The Cronbach's α coefficients were greater than 0.70 for all domains, and test-retest reliability coefficients were all greater than 0.80 exception of EWB 0.74 with the range of 0.81-0.96. The domains of PWB, FWB and the overall scale had significant changes after treatments with SRM ranging from 0.40 to 0.69. G-coefficients and Ф-coefficients confirmed the reliability of the scale further with exact variance components. Conclusion: The Chinese version of FACT-Hep can be used to measure HRQOL for patients with hepatocellular carcinoma in China with being of good psychometric properties.

Fields of Study & Subjects

Cancer survivorship and care Psychometric Methodologies and Testing Health Education and Validation

Publication details

Journal / source
Cancer Management and Research
Volume
Volume 18
Pages
1–12
Publication date
1 January 2026
Language
EN